Vector-borne diseases such as dengue and malaria affect hundreds of millions of people each year in subtropical and tropical areas of the world. Use of decision support systems to provide improved operational capacity for data management, analysis and interpretation is emerging as a promising novel approach to combat these and other neglected tropical vector-borne diseases. This effort is spearheaded by the Innovative Vector Control Consortium, which is funding the development of decision support systems for dengue (at Colorado State University) and malaria (at the Medical Research Council of South Africa). Our long-term goal is development of a flexible vector-borne disease decision support system with capacity for adaptation to any particular vector-borne disease or combination of diseases of local importance. Such a system needs to incorporate use of Controlled Vocabularies (sets of standardized and defined terms) and Ontologies (sets of standardized and defined controlled vocabulary terms and their inter-relationships). This will provide standardization of terminology, inform database schemas, facilitate linkage of data from fragmented databases (e.g., clinical and vector control data) and allow for compilation of data in local, regional or global databases. The latter will facilitate critical meta-analyses to determine which types of integrated vector and disease management strategies are most effective. Ontologies are increasingly developed, supported and used in biomedical science;the Open Biomedical Ontologies (OBO) Foundry (http://www.obofoundry.org/) is at the core of this process and has established a set of principles and standards for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. OBO Foundry candidate ontologies range in scope from tick gross anatomy (Tick Anatomy Ontology) to insecticide resistance (Mosquito Insecticide Resistance Ontology), infectious disease (Infectious Disease Ontology) and the environment (Environment Ontology). After a review of existing OBO candidate ontologies, we have identified the need for development of ontologies to address the topics of surveillance and management of arthropod vectors of human pathogens. Use of ontologies for vector surveillance and vector management in decision support systems for vector-borne diseases is a novel approach that will: 1) remedy the current use of nebulous vector surveillance and vector management terms without formal definitions and relationships, 2) improve data quality and data integration and 3) facilitate standardized monitoring and evaluation of vector control interventions. The goals of the project are to: " Develop and launch a web interface that provides easy access for subject matter experts to comment on proposed controlled vocabulary terms and their definitions. " Produce controlled vocabularies for vector surveillance and vector management. " Create candidate ontologies for vector surveillance (Vector Surveillance Ontology) and vector management (Vector Management Ontology). " Incorporate the Vector Surveillance Ontology and the Vector Management Ontology into the decision support system under development for dengue. The project will be delivered by a Colorado State University five-person team (Lars Eisen, Saul Lozano-Fuentes, Chester G. Moore, Marlize Coleman and Sanika Chitari) with broad expertise in Information Systems / Decision Support Systems and mosquito- and tick-borne diseases.